A physiologically motivated dynamical model of cardiovascular autonomic regulation successfully generated complex heart rate dynamics that statistically agreed with real-life data.
A dynamical model of cardiovascular autonomic regulation can successfully simulate complex heart rate dynamics in both health and disease states.
A physiologically motivated, dynamical model of cardiovascular autonomic regulation is shown to be capable of generating long-range correlated and multifractal heart rate. Virtual disease simulations are carried out systematically to account for the disease-induced relative dysfunction of the parasympathetic and the sympathetic branches of the autonomic control. Statistical agreement of the simulation results with those of real life data is reached, suggesting the possible use of the model as a state-of-the-art basis for further understanding of the physiological correlates of complex heart rate dynamics.
Kotani et al. (Wed,) conducted a other in Cardiovascular autonomic regulation in health and disease. Virtual disease simulations using a dynamical model of cardiovascular autonomic regulation vs. Real life data was evaluated on Statistical agreement of simulation results with real life data. A physiologically motivated dynamical model of cardiovascular autonomic regulation successfully generated complex heart rate dynamics that statistically agreed with real-life data.